The computation of word-level confidence estimates for the results produced by a speech recognition system has become a well-established practice. In general, each of these estimates indicates the probability that a particular word in the results is correct (that is, that the speaker actually said the word). Word-level confidence estimates have been applied to such tasks as spotting misrecognized or out-of-vocabulary words, rejecting recognition hypotheses in command-and-control environments, and controlling prompts for confirmation in computer-based dialogue systems. Techniques for determining word-level confidence estimates are described by L. Gillick, Y. Ito, and J. Young in “A Probabilistic Approach to Confidence Estimation and Evaluation,” Proc. ICASSP-97, pages 879–882 (1997), which is incorporated by reference.